Generating adaptive notification

ABSTRACT

A method for generating adaptive notifications include analyzing, at a user device, a spectrum of environmental noise. A portion of the spectrum for adaptive notification enhancement is selected based on the analyzing the spectrum of environmental noise. An adapted notification is generated at the user device by enhancing the selected portion of the spectrum. The adapted notification is transmitted at the user device.

TECHNICAL FIELD

This disclosure relates to generating notifications for communicationdevices and, more specifically, to generating adaptive notifications.

BACKGROUND

In some cases, a user device may provide notification functionalities. Anotification may be an audio output. For example, a user device maygenerate a sound when the user device receives an email or a text. Thesound may notify the user that an email or a text is received.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an example user device thatgenerates an adaptive notification according to an implementation.

FIG. 2 is a chart illustrating an example spectrum analysis of theenvironmental noise.

FIG. 3 is a chart illustrating an example spectrum analysis of anotification that collides with the environmental noise.

FIG. 4 is a chart illustrating an example spectrum analysis of anotification that does not collide with the environmental noise.

FIG. 5 is a flowchart illustrating an example method for generating anadaptive notification by a user device.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

The present disclosure is directed to generating adaptive notifications.In some cases, a user device may be positioned in a noisy environment.The environmental noise may be spread uniformly across the audiospectrum (shapeless), or concentrated in one or more narrow frequencybands (highly shaped). In some cases, a user may have difficulty hearinga notification over the noisy environment.

In some cases, volume of the notification may be boosted to overcome theenvironmental noise. However, in some cases, boosting the volumes of thenotifications may not be efficient or effective. For example, thedominant frequencies of the notification and the noise may coincide.While boosting the volume of the notification increases the amplitudeuniformly across the frequency region, the increased amplitude of thedominant frequency of the notification may not be able to overcome thepower of the noise at the same frequency regions. Thus, the notificationmay not be recognizable by the user. Furthermore, if the high powerportion of the noise has a narrow bandwidth, boosting the volume of thenotification may cause the notification to play at an un-necessarilyhigh volume and create a bad user experience.

In some cases, an adaptive notification may be generated by measuringand analyzing the spectrum of the environmental noise. A portion of thespectrum that corresponds to low noise power may be identified forenhancement. An adaptive notification may be generated by enhancing theidentified portion. In some cases, the enhancement may be based on acontext of the notification. FIGS. 1-5 and associated descriptionsprovide additional details of these implementations.

Generating the adaptive notification according to methods and systemsdescribed herein may provide one or more advantages. For example, byenhancing the portion of the spectrum corresponding to low noise power,the adaptive notification may provide a recognizable audio output overthe environmental noise without significantly increasing the overallvolume of the notification. This approach may create a better userexperience and reduce power consumption of the user device. Furthermore,by associating the enhancement with a context of the notification, theuser may recognize the context of the notification based on the audiooutput of the notification, without looking at the device. Otheradvantages will be apparent to those of ordinary skill in the art.

FIG. 1 is a block diagram illustrating an example user device 100 thatgenerates an adaptive notification according to an implementation. Asillustrated, the example user device 100 includes a spectrum analyzingmodule 122 and an adaptive notification generation module 124. Theexample user device 100 also includes a processing unit 102, a wirelesscommunication subsystem 106, a user interface 110, and a memory 104.

The user interface 110 represents one or more hardware modules, one ormore software modules, or a combination thereof that can be configuredto provide an input and output interface for the user device 100. Theuser interface 110 can include, for example, one or more of a screen ortouch screen (for example, a liquid crystal display (LCD), a lightemitting display (LED), an organic light emitting display (OLED), or amicro-electromechanical system (MEMS) display), a keyboard or keypad, atrackball, or a combination thereof

As illustrated, the user interface 110 includes an audio system 112. Theaudio system 112 represents one or more hardware modules, one or moresoftware modules, or a combination thereof that can be used to transmitthe adaptive notification as an audio output. For example, the audiosystem 112 may include a speaker.

The user interface 110 also includes a microphone 114. The microphone114 represents one or more hardware modules, one or more softwaremodules, or a combination thereof that can be used to sense theenvironment and measure the environmental noise. In some cases, themicrophone 114 may measure the environmental noise by periodicallycollecting audio inputs of the environment. In some cases, themicrophone 114 may be a digital microphone. Alternatively or incombination, the microphone 114 may be an analog microphone. In somecases, the microphone 114 may be configured in an “always on” mode,where the microphone 114 can continuously measure the environmentalnoise. Alternatively or in combination, the microphone 114 can measurethe environmental noise according to a measurement cycle. In some cases,the measurement cycle may be configured by the spectrum analyzing module122 based on the movement of the user device. The following paragraphsprovide additional details of the measurement cycle.

As illustrated, the user device 100 includes the spectrum analyzingmodule 122. The spectrum analyzing module 122 represents one or morehardware modules, one or more software modules, or a combination thereofthat can be configured to receive the measurement from the microphone114 and analyze the spectrum of the environmental noise.

In some cases, the spectrum analyzing module 122 may configure ameasurement cycle for the microphone 114 to measure the environmentalnoise. For example, the spectrum analyzing module 122 may configure therate and resolution of the audio data collection of the environmentbased on the measurement cycle. In some cases, measurement cycle may beconfigured based on the moving pattern of the user device 100. Forexample, the user device 100 may include a motion sensor unit used todetect the motion pattern of the user device 100. In some cases, themotion sensor unit may track the location of the user device 100 using,e.g., a Global Position System (GPS) module or an assisted-GPS module,and estimate the speed of the user device 100. The spectrum analyzingmodule 122 may configure the measurement cycle based on the estimatedspeed. For example, if the user device 100 is stationary or moves at alow speed, then the noise of the environment may change slowly.Therefore, the measurement cycle may include an increased delay betweeneach measurement, a reduced resolution, or a combination thereof. If, onthe other hand, the user device 100 moves at a high speed, then thenoise of the environment may change quickly. Therefore, the measurementcycle may include a reduced delay between each measurement, an increasedresolution, or a combination thereof

In some cases, the spectrum analyzing module 122 may configure themeasurement cycle based on the change of the environmental noise. Forexample, the spectrum analyzing module 122 may store the analyzedspectrum of the environmental noise based on the previous measurement.The spectrum analyzing module 122 may compare the analyzed spectrum ofthe environmental noise based on the current measurement with the storedspectrum based on the previous measurement to determine how fast theenvironmental noise changes. If the environmental noise changes fastover time, the spectrum analyzing module 122 may reduce the delaybetween each measurement, increase the resolution of the measurement, ora combination thereof. If, on the other hand, the environmental noisechanges slowly over time, the spectrum analyzing module 122 may increasethe delay between each measurement, reduce the resolution of themeasurement, or a combination thereof.

Configuring the measurement cycle based on the movement and/or thechanges of the environmental noise may provide one or more advantages.For example, when the environment changes slowly, the power consumptionof the user device 100 used for measuring and processing environmentalnoise may be reduced without affecting the accuracy of the measurement.

The spectrum analyzing module 122 may receive the measurement data fromthe microphone 114 and perform a spectrum analysis of the environmentalnoise. FIG. 2 is a chart 200 illustrating an example spectrum analysisof the environmental noise. As shown in FIG. 2, the power distributionof the noise is uneven throughout the spectrum. In some bands, e.g.,between 200 Hz and 1 KHz, the power level of the noise is high. In somebands, e.g., between 1 KHz and 10 KHz, the power level of the noisereduces as the frequency increases. In some bands, e.g., between 10 KHzand 20 KHz, the power level of the noise is low. In some cases, thespectrum analyzing module 122 may identify a portion of the spectrumthat represents low power level of the noise. The identified portion maybe used for adaptive notification enhancement. In some cases, theidentification may be based on a predetermined power level. The spectrumanalyzing module 122 may identify the portion of the spectrum where thepower level of the noise is below the predetermined power level as acandidate portion of the spectrum for enhancement. For example, thepredetermined power level may be −48 dB, and the identified portion mayinclude frequency bands above 3.2 KHz.

In some cases, the spectrum analyzing module 122 may configure themeasurement based on the power of the noise. For example, if the longterm root mean square (RMS) of the noise power level is below athreshold, the spectrum analyzing module 122 may configure themeasurement cycle to include an increased delay between the measurementsto save power.

Referring back to FIG. 1, the user device 100 includes the adaptivenotification generation module 124. The adaptive notification generationmodule 124 represents one or more hardware modules, one or more softwaremodules, or a combination thereof that can be configured to generate anadaptive notification based on the spectrum analysis of theenvironmental noises.

In some cases, the adaptive notification generation module 124 maygenerate an adaptive notification that has a high power level in thefrequency bands where the noise power level is low. Therefore, theadaptive notification does not collide with the noise, and a user of theuser device 100 may hear the notification more easily. FIG. 3 is a chart300 illustrating an example spectrum analysis of a notification thatcollides with the environmental noise. As illustrated, the notificationhas a high power level below 1 KHz and low power level beyond 3 KHz,which is similar to the environmental noise illustrated in FIG. 2.Therefore, the high power portion of the notification may collide withthe high power level of the noise and the user may not be able todiscern the notification from the background noise. FIG. 4 is a chart400 illustrating an example spectrum analysis of a notification thatdoes not collide with the environmental noise. As illustrated, thenotification has a high power level in frequency bands around 2 KHz, 5KHz, and 10 KHz, which is different than the environmental noiseillustrated in FIG. 2. Therefore, the high power portion of thenotification does not collide with the high power level of the noise andthe user may be able to detect the notification over the backgroundnoise.

Referring back to FIG. 1, in some cases, the adaptive notificationgeneration module 124 may select a base notification and generate theadaptive notification by enhancing the frequency bands of the basenotification corresponding to low noise power. For example, the adaptivenotification generation module 124 may select an enhanced waveform. Theadaptive notification generation module 124 may add the enhancedwaveform to the base notification to generate the adaptive notification.In some cases, the adaptive notification generation module 124 mayselect an enhanced waveform that has a high power level in the frequencybands corresponding to the low power level of the noise. Alternativelyor in combination, the adaptive notification generation module 124 mayadd the enhanced waveform to the frequency bands of the basenotification that corresponds to the low power level of the noise.

In some cases, the adaptive notification generation module 124 mayselect the waveforms based on context of the notification. In oneexample, the context may be a source context. Examples of sourcecontexts may be email, text, voicemail, application, or any othercontext that is associated with the source of the notification. Eachsource context may correspond to a different waveform. Therefore, theadaptive notification generation module 124 may determine the source ofthe notification, and select the waveform that corresponds to the sourcecontext of the notification. By including the waveform that correspondsto the source context of the notification, the user may know the sourceof the notification, e.g., whether the notification is an email, a text,a voicemail, an application, from the audio output of the notification.In some cases, the source context may include a source address of theadaptive notification. The source address may be an email address, aphone number, or any other addresses that identifies the addressassociated with the notification. Therefore, the audio output of theadaptive notification may indicate the caller of the voice call or thesending of the email that triggers the notification. In some cases, theassociations between different waveforms and the respective sourcecontexts may be configurable by a user of the user device 100.

In another example, the context may be an event context. Examples ofevent contexts may be a calendar event, a task, or a deadline thattriggers the notification. Each event context may correspond to adifferent waveform. Therefore, the adaptive notification generationmodule 124 may determine the event that triggers the notification andselect the waveform that corresponds to the event context of thenotification. In some cases, a user may configure different waveformsfor different event occurrences. For example, a waveform may beassociated with an external meeting with a client, and a differentwaveform may be associated with an internal meeting. Therefore, theaudio output of the adaptive notification may indicate the event thattriggers the notification. In some cases, the associations betweendifferent waveforms and the respective event contexts may beconfigurable by a user of the user device 100.

In yet another example, the context may be an urgency context. Theurgency context may indicate the time urgency of the notification, theimportance of the notification, or a combination thereof. For example,the urgency context may indicate that the notification is for a meetingthat would occur in 30 minutes, 15 minutes, or 5 minutes. The urgencycontext may also indicate that the notification has a high, medium, orlow importance. Different waveforms may be associated with differenturgency context. The adaptive notification generation module 124 maydetermine the urgency of the notification and select the waveform thatcorresponds to the urgency context of the notification. For example, awaveform with increased volume or pitch may be selected for a moreurgent notification. Therefore, the audio output of the adaptivenotification may indicate the urgency of the notification. In somecases, the associations between different waveforms and the respectiveurgency contexts may be configurable by a user of the user device 100.

In some cases, the adaptive notification generation module 124 may useone or more sonic layers to generate the adaptive notification. Forexample, the enhanced waveforms may be stored in a wavetable thatincludes a plurality of sonic layers. Each sonic layer may be associatedwith a respective type of context. For example, the wavetable mayinclude 3 sonic layers. The first layer is associated with the sourcecontext. The second layer is associated with the event context. Thethird layer is associated with the urgency context. The sonic layers maybe orthogonal to one another. Therefore, waveforms from multiple soniclayers may be added together to indicate multiple contexts associatedwith the notification.

For example, the adaptive notification generation module 124 may selecta first waveform that corresponds with the source context of thenotification from the first sonic layer, a second waveform thatcorresponds with the event context of the notification from the secondsonic layer, and a third waveform that corresponds with the urgencycontext of the notification from the third sonic layer. The adaptivenotification generation module 124 may add the first, the second, andthe third waveform to generate the enhanced waveform. The adaptivenotification generation module 124 may add the enhanced waveform to thebase notification to generate the adaptive notification.

In some cases, the adaptive notification generation module 124 may useDSP (Digital Signal Processing) techniques to generate the adaptivenotification. In some cases, the DSP algorithms can be used to generateoptimum audio synthetic layers from an original source audio by creatingartificial layers via re-sampling. For example, the adaptivenotification generation module 124 may use DSP algorithms to generatethe adaptive notification by positioning the high power level componentof the base notification in the frequency bands that correspond to lownoise power of the environment.

Alternatively or in combination, the adaptive notification generationmodule 124 may distort the waveform of the base notification based oncontext associated with the notification. For example, the adaptivenotification generation module 124 may use DSP algorithms to increasethe pitch or the volume of selected frequency bands based on the sourcecontext, the event context, the urgency context, or any other contexts.In one example, the adaptive notification generation module 124 mayincrease the pitch for a notification with high urgency and decrease thepitch for a notification with low urgency. In some cases, theassociation between different DSP distortion techniques and therespective contexts may be configurable by a user.

As illustrated, the user device 100 includes the memory 104. The memory104 represents one or more hardware modules, one or more softwaremodules, or a combination thereof that may be configured to storecomputer-readable information. Examples of the memory 104 may includeRandom-access memory (RAM), Read-only memory (ROM), or flash memory. Thememory 104 can store an operating system (OS) of the user device 100,and various other computer-executable instructions, logic or softwareprograms for performing one or more of the processes, steps, or actionsdescribed above.

As illustrated, the memory 104 can store base notifications 132 andenhanced waveforms 134. As discussed previously, the adaptivenotification generation module 124 may select one of the basenotifications 132 and enhance the selected base notification accordingto the spectrum analysis of the environmental noise, the context of thenotification, and a combination thereof In some cases, the adaptivenotification generation module 124 may select one or more enhancedwaveforms 134 to generate the adaptive notification. In some cases, theenhanced waveforms 134 may be associated with one or more sonic layers.

In some cases, the memory 104 may also store the spectrum analysis ofthe environmental noise. As discussed previously, the spectrum analyzingmodule 122 may compare the spectrum analysis from different measurementsto configure the measurement cycle.

As illustrated, the user device 100 includes the processing unit 102.The processing unit 102 can include one or more processing components(alternatively referred to as “processors” or “central processing units”(CPUs)) configured to execute instructions related to one or more of theprocesses, steps, or actions described herein in connection with one ormore of the implementations disclosed herein. In some implementations,the processing unit 102 may be configured to generate controlinformation, such as a measurement report, or respond to receivedinformation, such as control information from a network node. Theprocessing unit 102 may also be configured to make a Radio ResourceManagement (RRM) decision such as cell selection/reselection informationor trigger a measurement report.

As illustrated, the user device 100 includes the wireless communicationsubsystem 106. The wireless communication subsystem 106 may beconfigured to provide wireless communication for voice, data, and/orcontrol information provided by the processing unit 102. The wirelesscommunication subsystem 106 can include, for example, one or moreantennas, a receiver, a transmitter, a local oscillator, a mixer, and adigital signal processing (DSP) unit. In some implementations, thesubsystem 106 can support multiple-input multiple-output (MIMO)transmissions. In some implementations, the receiver in the wirelesscommunication subsystems 106 can be an advance receiver or a baselinereceiver. Two receivers can be implemented with identical, similar, ordifferent receiver processing algorithms. In some cases, the wirelesscommunication subsystem 106 can be configured to transmit and receivedata using Global System for Mobile communication (GSM), InterimStandard 95 (IS-95), Universal Mobile Telecommunications System (UMTS),CDMA2000 (Code Division Multiple Access), Evolved Universal MobileTelecommunications System (E-UMTS), Long Term Evaluation (LTE),LTE-Advanced, or any other radio access technology.

Turning to a general description of the elements, a user device may bereferred to as mobile electronic device, user device, mobile station,subscriber station, portable electronic device, mobile communicationsdevice, wireless modem, or wireless terminal. Examples of a user device(e.g., the user device 100) may include a cellular phone, personal dataassistant (PDA), smart phone, laptop, tablet personal computer (PC),pager, portable computer, portable gaming device, wearable electronicdevice, or other mobile communications device having components forcommunicating voice or data via a wireless communication network. Thewireless communication network may include a wireless link over at leastone of a licensed spectrum and an unlicensed spectrum.

Other examples of a user device include mobile and fixed electronicdevice. A user device may include a Mobile Equipment (ME) device and aremovable memory module, such as a Universal Integrated Circuit Card(UICC) that includes a Subscriber Identity Module (SIM) application, aUniversal Subscriber Identity Module (USIM) application, or a RemovableUser Identity Module (R-UIM) application. The term “user device” canalso refer to any hardware or software component that can terminate acommunication session for a user. In addition, the terms “userequipment,” “UE,” “user equipment device,” “user agent,” “UA,” “userdevice,” and “mobile device” can be used synonymously herein.

While elements of FIG. 1 are shown as including various component parts,portions, or modules that implement the various features andfunctionalities, nevertheless these elements may instead include anumber of sub-modules, third-party services, components, libraries, andsuch, as appropriate. Furthermore, the features and functionality ofvarious components can be combined into fewer components as appropriate.

FIG. 5 is a flowchart illustrating an example method 500 for generatingan adaptive notification by a user device. The method 500 may begin atblock 502, where environmental noise is measured. In some cases, theenvironmental noise may be measured by a microphone. At block 504, thespectrum of the measured environmental noise is analyzed. At block 506,the spectrum of the measured environmental noise is classified. In somecases, a portion of the spectrum of the measured environmental noisethat have low power may be identified. In some cases, the user devicemay store the spectrum analysis of the environmental noise.

At block 508, the analysis of the environmental noise may be updated. Insome cases, the microphone may be turned into an “always-on” mode tomeasure the environmental noise continuously. In some cases, theenvironmental noise may be measured according to a measurement cycle.For example, the user device may detect a motion pattern of the userdevice and determine the measurement cycle based on the detected motionpattern. In some cases, the user device may update the environmentalnoise after each measurement. For example, after a measurement, the userdevice may compare the spectrum analysis based on the currentmeasurement with the analysis based on the pervious measurement. If thelow power portion of the spectrum has changed, the user device mayupdate the stored spectrum analysis.

At block 510, an adapted notification is generated. In some cases, theadapted notification is generated based on the spectrum analysis of theenvironmental noise. For example, the user device may select a basenotification. The user device may select an enhanced waveform and addthe selected enhanced waveform to the base notification to generate theadapted notification. The selected enhanced waveform may be added on theportion of the spectrum that is identified as having low environmentalnoise.

In some cases, the enhanced waveform may be selected from a plurality ofpredetermined waveforms. In some cases, the selection of the enhancedwaveform is based on a context of the notification. In some cases, theplurality of the predetermined waveforms may be organized in one or moresonic layers, each sonic layer corresponding to a category of context.Examples of the category may include a source context, an urgencycontext, and an event context. In some cases, the user device may selecta first waveform from a first sonic layer based on the source context ofthe notification, a second waveform from a second sonic layer based onthe event context of the notification, and a third waveform from a thirdsonic layer based on the urgency context of the notification.

At block 512, the user device transmits the adapted notification.

While operations are depicted in the drawings in a particular order,this should not be understood as requiring that such operations beperformed in the particular order shown or in sequential order, or thatall illustrated operations be performed, to achieve desirable results.In certain circumstances, multitasking and parallel processing may beemployed. Moreover, the separation of various system components in theimplementation described above should not be understood as requiringsuch separation in all implementations, and it should be understood thatthe described program components and systems can generally be integratedtogether in a signal software product or packaged into multiple softwareproducts.

Also, techniques, systems, subsystems, and methods described andillustrated in the various implementations as discrete or separate maybe combined or integrated with other systems, modules, techniques, ormethods. Other items shown or discussed as coupled or directly coupledor communicating with each other may be indirectly coupled orcommunicating through some interface, device, or intermediate component,whether electrically, mechanically, or otherwise. Other examples ofchanges, substitutions, and alterations are ascertainable by one skilledin the art and could be made.

While the above detailed description has shown, described, and pointedout the fundamental novel features of the disclosure as applied tovarious implementations, it will be understood that various omissions,substitutions, and changes in the form and details of the systemillustrated may be made by those skilled in the art. In addition, theorder of method steps are not implied by the order they appear in theclaims.

What is claimed is:
 1. A method, comprising: analyzing, at a userdevice, a spectrum of environmental noise; selecting, based on analyzingthe spectrum of environmental noise, a portion of the spectrum foradaptive notification enhancement, wherein a power level of theenvironmental noise in the selected portion of the spectrum is less thana predetermined power level; generating, at the user device, an adaptednotification by enhancing a notification on the selected portion of thespectrum; and transmitting, at the user device, the adaptednotification.
 2. The method of claim 1, wherein generating the adaptednotification comprises: selecting an enhanced waveform from a pluralityof predetermined waveforms; and adding the selected enhanced waveform toa notification waveform to generate the adapted notification.
 3. Themethod of claim 2, wherein the enhanced waveform is selected based on acontext of the notification.
 4. The method of claim 3, wherein thecontext is at least one of a source context or an urgency context. 5.The method of claim 2, wherein each of the plurality of predeterminedwaveforms is associated with at least one of a plurality of soniclayers, and each of the plurality of sonic layers is associated with acontext.
 6. The method of claim 1, wherein analyzing the spectrum ofenvironmental noise comprises measuring a frequency distribution ofenvironmental noise using a digital microphone.
 7. The method of claim6, further comprising: detecting a motion pattern of the user device;determining a measurement cycle based on the detected motion pattern;and measuring the frequency distribution according to the measurementcycle.
 8. A tangible, non-transitory machine-readable medium encodedwith machine-executable instructions, wherein execution of themachine-executable instructions causes a computing device to performoperations comprising: analyzing a spectrum of environmental noise;selecting, based on analyzing the spectrum of environmental noise, aportion of the spectrum for adaptive notification enhancement, wherein apower level of the environmental noise in the selected portion of thespectrum is less than a predetermined power level; generating an adaptednotification by enhancing a notification on the selected portion of thespectrum; and transmitting the adapted notification.
 9. The tangible,non-transitory machine-readable medium of claim 8, wherein generatingthe adapted notification comprises: selecting an enhanced waveform froma plurality of predetermined waveforms; and adding the selected enhancedwaveform to a notification waveform to generate the adaptednotification.
 10. The tangible, non-transitory machine-readable mediumof claim 9, wherein the enhanced waveform is selected based on a contextof the notification.
 11. The tangible, non-transitory machine-readablemedium of claim 10, wherein the context is at least one of a sourcecontext or an urgency context.
 12. The tangible, non-transitorymachine-readable medium of claim 8, wherein analyzing the spectrum ofenvironmental noise comprises measuring a frequency distribution ofenvironmental noise using a digital microphone.
 13. The tangible,non-transitory machine-readable medium of claim 12, wherein theoperations further comprise: detecting a motion pattern of the computingdevice; determining a measurement cycle based on the detected motionpattern; and measuring the frequency distribution according to themeasurement cycle.
 14. A device, comprising: a memory; and at least onehardware processor communicatively coupled with the memory andconfigured to: analyze, at the device, a spectrum of environmentalnoise; select, based on analyzing the spectrum of environmental noise, aportion of the spectrum for adaptive notification enhancement, wherein apower level of the environmental noise in the selected portion of thespectrum is less than a predetermined power level; generate, at thedevice, an adapted notification by enhancing a notification on theselected portion of the spectrum; and transmit, at the device, theadapted notification.
 15. The device of claim 14, wherein generating theadapted notification comprises: selecting an enhanced waveform from aplurality of predetermined waveforms; and adding the selected enhancedwaveform to a notification waveform to generate the adaptednotification.
 16. The device of claim 15, wherein the enhanced waveformis selected based on a context of the notification.
 17. The device ofclaim 16, wherein the context is at least one of a source context or anurgency context.
 18. The device of claim 15, wherein each of theplurality of predetermined waveforms is associated with at least one ofa plurality of sonic layers, and each of the plurality of sonic layersis associated with a context.
 19. The device of claim 14, furthercomprising a digital microphone, and wherein analyzing the spectrum ofenvironmental noise comprises measuring a frequency distribution ofenvironmental noise using the digital microphone.
 20. The device ofclaim 19, further comprising a motion sensor that is configured todetect a motion pattern of the device, and wherein the at least onehardware processor is further configured to: determine a measurementcycle based on the detected motion pattern; and measure the frequencydistribution according to the measurement cycle.